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Automated Diagnostic System for Laryngeal Hemiplegia Using Endoscopic Image

Md. Musfequs Salehin, Lihong Zheng, and Junbin Gao
School of Computing & Mathematics, Charles Sturt University, Australia
Abstract—Laryngeal hemiplegia is a naturally occurringdisease of a horse recognized as a common reason of thepoor performance. This syndrome is diagnosed by a humanthrough an endoscopic observation. The asymmetry ofarytenoid cartilages is calculated by left to right anglequotients (LRQ). However, human inspection maymisdiagnose the disease. Therefore, an automatic diagnosticsystem is expected to analysis the asymmetric view oflaryngeal hemiplegia. In this paper, we have proposed anautomatic way to analysis laryngeal hemiplegia bycombining image segmentation and parabola fittingalgorithms. Our method includes six steps: (1) hierarchicalcontour map is achieved by a state-of-the-art hierarchicalimage segmentation method joining Global Probability ofBoundary (gPb), Oriented Watershed Transform (OWT),and Ultrametric Contour Map (UCM); (2) key curves areextracted; (3) boundaries are confirmed by Parabola fittingmethod; (4) dorsal-most point of rima glottidis is selected; (5)proximal-most point is identified and (6) LRQ is calculatedas the final measurement. To evaluate the accuracy of ourproposed method, a dataset of horse larynx endoscopicimages has been built up and tested. Experimental resultshave shown that the proposed method has goodperformance.

Index Terms—horse larynx, endoscopic image, hierarchicalsegmentation, corner detection, LRQ calculation

Cite: Md. Musfequs Salehin, Lihong Zheng, and Junbin Gao, "Automated Diagnostic System for Laryngeal Hemiplegia Using Endoscopic Image," International Journal of Signal Processing Systems,  Vol. 1, No. 1, pp. 79-83,  June 2013. doi: 10.12720/ijsps.1.1.79-83
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